Page Reader AI | Exam Professional Machine Learning Engineer topic 1 question 260 discussion

Exam Professional Machine Learning Engineer topic 1 question 260 discussion - ExamTopics

AI Summary Hide AI Generated Summary

Problem:

The task involves developing a model to predict machine part failures using a multivariate time series dataset. The goal is to effectively log data and track artifacts from various preprocessing and modeling approaches within a Vertex AI Workbench notebook.

Options:

Option A: Uses log_time_series_metrics for preprocessed data and log_merrics for loss values (incorrect spelling).
Option B: Uses log_time_series_metrics for preprocessed data and log_metrics for loss values.
Option C: Uses TensorBoard, assign_input_artifact for preprocessed data, and log_time_series_metrics for loss values.
Option D: Uses TensorBoard and log_time_series_metrics for both preprocessed data and loss values.

Solution:

The correct answer is B. Option B accurately utilizes Vertex AI's functionalities by creating an experiment, setting up ML Metadata, using log_time_series_metrics for time-series data tracking, and log_metrics for logging loss values. Other options either have spelling errors, mismatched function usage or unnecessary use of TensorBoard for this specific task.

You are developing a model to predict whether a failure will occur in a critical machine part. You have a dataset consisting of a multivariate time series and labels indicating whether the machine part failed. You recently started experimenting with a few different preprocessing and modeling approaches in a Vertex AI Workbench notebook. You want to log data and track artifacts from each run. How should you set up your experiments?

A. 1. Use the Vertex AI SDK to create an experiment and set up Vertex ML Metadata. 2. Use the log_time_series_metrics function to track the preprocessed data, and use the log_merrics function to log loss values.
B. 1. Use the Vertex AI SDK to create an experiment and set up Vertex ML Metadata. 2. Use the log_time_series_metrics function to track the preprocessed data, and use the log_metrics function to log loss values.
C. 1. Create a Vertex AI TensorBoard instance and use the Vertex AI SDK to create an experiment and associate the TensorBoard instance. 2. Use the assign_input_artifact method to track the preprocessed data and use the log_time_series_metrics function to log loss values.
D. 1. Create a Vertex AI TensorBoard instance, and use the Vertex AI SDK to create an experiment and associate the TensorBoard instance. 2. Use the log_time_series_metrics function to track the preprocessed data, and use the log_metrics function to log loss values.

Show Suggested Answer Hide Answer

Was this article displayed correctly? Not happy with what you see?

See Archived Versions